Anyscale
Scalable AI with Ray
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General Infrastructure Scalable AI with Ray
Running distributed AI workloads using Ray, the open-source framework for scaling Python across clusters. It's used for distributed training, hyperparameter tuning, batch inference, and serving — particularly when workloads need to scale beyond a single GPU node.
Sign up at anyscale.com to get a managed Ray cluster, or install Ray locally with pip install ray. For cloud use, connect your AWS or GCP account and Anyscale manages the cluster lifecycle. Submit jobs via the Anyscale CLI or SDK, specifying GPU requirements in your Ray resource configs.
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